In a wireless communication system, a Power Amplifier (PA) used for a Radio Frequency (RF) stage requires linear characteristics. In the PA, the linear characteristics may provide not only a signal level allowable in an adjacent channel, but also a small Error Vector Magnitude (EVM). The signal level allowable in an adjacent channel may represent, for example, an Adjacent Channel Leakage Ratio (ACLR). The ACLR means a difference between power of the center channel and power of an adjacent channel which is apart from the center channel by a specific offset frequency, and the ACLR is an index indicating linearity of the PA.
Every time the PA operates with a high efficiency, it linear characteristics may rapidly change to nonlinear characteristics, causing distortion of output signals. A DPD algorithm is used to compensate for the distortion of output signals.
Reference will be made to FIGS. 1A to 1C to describe the concept of the common DPD algorithm.
FIG. 1A illustrates ideal linear characteristics 101 between an input and an output of a PA. In FIG. 1A, an input of the PA may be almost the same as an output thereof, or may be different from the output by a scaling factor K. FIG. 1B illustrates nonlinear distortion 103 in an actual operation of a PA. In FIG. 1B, an output of a PA may be represented as a function F related to an input thereof.
The nonlinear distortion 103 as shown in FIG. 1B may degrade the quality of in-band signals, and cause significant out-of-band distortion. In order to compensate for the nonlinear distortion, the DPD algorithm may pre-distort a signal to be input to a PA so that an output of the PA may be linear. FIG. 1C illustrates an example of distortion 105 that is opposite to the nonlinear distortion 103 in FIG. 1B and is applied to an input signal.
FIG. 2 illustrates an example of an apparatus in which a DPD unit is coupled to an input of a PA.
In FIG. 2, a DPD unit 210 may apply distortion 201 that is opposite to nonlinear distortion 203, to an input signal at a front stage of a PA 230. Then, the nonlinear distortion 203 occurring in the PA 230 may be compensated (or removed) for by the opposite distortion 201, so a signal having linear characteristics 205 may be output at the PA 230. The opposite distortion 201 will be referred to herein as pre-distortion.
The common DPD algorithm, as described above, may easily compensate for signal distortion, for the signal whose signal level slowly changes. However, it is well known to those skilled in the art that for the signal whose signal level rapidly changes, the common DPD algorithm may not stably compensate for the signal distortion. The ‘signal level’ refers to a power level of the signal.
Generally, DPD parameters (also known as DPD information) for performing the pre-distortion according to the DPD algorithm may be used in the DPD unit 210 in FIG. 2. The DPD parameters may be estimated using captured signals. A plurality of signals which are captured from both of an input terminal and an output terminal of a PA may be used as the captured signals. Therefore, DPD performance may depend on the captured signals.
If a level of the captured signals is very low, the DPD unit 210 may not estimate DPD parameters for pre-distortion, with respect to magnitudes of signals in the full range.
Reference will now be made to FIGS. 3 and 4, to describe DPD characteristics that estimation of DPD parameters is limited by the maximum magnitude of a signal in a DPD algorithm.
Referring to FIG. 3, if the maximum magnitude of a captured signal is represented by reference numeral 301, the region may be divided, on the basis of the maximum magnitude 301 of the captured signal, into a region 303 where the DPD parameters can be estimated and a region 305 where the DPD parameters are unknown or cannot be estimated. The maximum magnitude of the captured signal means the maximum power level of the signal. In the DPD algorithm, DPD parameters estimated for any signal level (or signal magnitude) may be applied to a signal that has a power level lower than (or similar to) the signal level, but may not be applied to a signal that has a power level higher than the signal level.
Referring to FIG. 4, the x-axis represents a time, the y-axis represents a signal magnitude, and DPD parameters are assumed to be estimated from a signal that is captured in, for example, a part “3” 401 in the time axis. In this case, the DPD algorithm may successfully estimate DPD parameters in parts “2”, “4”, “5” and “6” having a signal level lower than or equal to the signal level of the part “3” 401. However, in parts “1” 403 and “7” 405 having a signal level higher than the signal level of the part “3” 401, the DPD algorithm may not estimate DPD parameters due to the DPD characteristics that estimation of DPD parameters is limited by the maximum magnitude of a signal.
A variety of DPD algorithms have been proposed, which can stably estimate DPD parameters even when the signal level changes abruptly in a DPD process as in the example of FIG. 4.
As regards an example of a DPD apparatus based on the existing DPD algorithm, the DPD apparatus may capture input/output signals at each of an input terminal and an output terminal of a PA. As for the captured signals, small parts of the original signal may be captured, and the DPD apparatus may perform validation determination for determining whether DPD parameters extracted from the captured signals are valid. The validation determination may be performed by comparing characteristics (hereinafter referred to as ‘long-term characteristics’) of signals captured for a long term with characteristics (hereinafter referred to as ‘short-term characteristics’) of signals captured for a short term. As for the long term and the short term, if a capture time for signals is longer than or equal to a predetermined time, the capture time may be defined as the long term, and if the capture time is shorter than or equal to a predetermined time, the capture time may be defined as the short term. The validation determination may be performed based on the signal level (e.g., signal power), Probability Density Function (PDF) and the like. The DPD apparatus may perform pre-distortion on the signals input to the PA, by estimating DPD parameters (or by performing DPD parameter estimation) from the signals that have passed the validation determination, among the captured signals.
FIG. 5 illustrates an example of capturing signals in a DPD apparatus based on the existing DPD algorithm, in which it is assumed that signals for estimation of DPD parameters are captured in a long-term measurement period 510. Signals captured in the example of FIG. 5 may be separated into signals 501 and 505 having a higher signal level and signals 503 having a lower signal level, depending on their signal levels. If the limitation by the maximum magnitude of a signal, which has been described in conjunction with FIGS. 3 and 4, is considered, the DPD apparatus in the example of FIG. 5 may determine the captured signals 501 having a higher signal level in each long-term measurement period 510 as signals valid for DPD parameter estimation, and determine the captured signals 503 having a lower signal level as signals invalid for DPD parameter estimation. Therefore, the DPD apparatus may estimate DPD parameters using only the captured signals 501 having a higher signal level in each long-term measurement period 510.
However, if DPD parameters are estimated in the long-term estimation period as in the example of FIG. 5, the DPD parameters may not be properly updated, in the case where an interval having a lower signal level is long in the long-term measurement period as shown by reference numeral 503.
FIG. 6 illustrates another example of capturing signals in a DPD apparatus based on the existing DPD algorithm, in which it is assumed that signals for estimation of DPD parameters are captured in long-term measurement periods 610a and 610b which are shorter than the long-term measurement period 510 in FIG. 5. Signals captured in the example of FIG. 6 may be separated into signals 611, 613 and 617 having a lower signal level and signals 615 having a higher signal level, depending on their signal levels. In the example of FIG. 6, DPD parameter update may be performed even in the long-term measurement period 610b, ensuring a more stable DPD operation compared with that in the example of FIG. 5.
However, in the example of FIG. 6, if there are signals having a high signal level as shown by reference numeral 619 in the next burst after the long-term measurement period 610b, a stable DPD operation may not be performed due to the limitation by the maximum magnitude of a signal.
Therefore, if a signal level of captured signals rapidly changes, the DPD apparatus based on the existing DPD algorithm may not guarantee a stable DPD operation. In consideration of these and other problems, a DPD algorithm has been proposed, which stores a plurality of sets of signal level-specific DPD parameters as table information, and performs a DPD operation by switching a set of DPD parameters to correspond to the signal level.
However, the DPD algorithm that uses a plurality of sets of DPD parameters should frequently switch the set of DPD parameters depending on the signal level, and the frequency switching may cause nonlinear distortion which is undesirable in a DPD operation. In addition, since this DPD algorithm requires a plurality of sets of DPD parameters, its DPD apparatus may be higher in complexity than a DPD apparatus based on a DPD algorithm that uses a single set of DPD parameter.
The above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present disclosure.